We are measuring and classifying breathing patterns in three types of healthy young adults at altitudes up to 14,000 ft., patients in a cardiac ICU and infants. The infants fall into four categories: premature, normal term neonates, those deemed at risk for SIDS, normal age cohorts for the previous category. Breathing data on adults are taken by a magnetometer technique which preserves naivete. A means of modifying this technique for use on infants is being explored. The long term objective is to provide a tool for the diagnosis of abnormal respiratory control function by relating breathing patterns to states of disease in adult patients or to risk of SIDS in infants. By breathing patterns we mean the aggregation of all oscillatory or pseudo-oscillatory variations appearing in the descriptors of individual breaths (i.e., inspiratory and expiratory durations and volumes, FRC, and ventilation). The breathing patterns are characterized by the strength and cycle time of the several oscillatory components imbedded within the time histories of each breath descriptor, and especially the relative amplitude and phase relationships between generically similar oscillatory components occurring in the concurrent time histories of different breath descriptors. In conjunction with our ultimate objective we are also investigating the effect of periodic breathing patterns on gas exchange processes and the muscular cost of breathing. To date we have developed and used a computer model of the respiratory system to predict that gas exchange need not be impaired, and have analytically computed that muscular effort can be slightly reduced. Our computer model can eventually lead to a significantly improved, continuous, non-invasive technique for clinically-monitoring cardiac output since our model can use the dramatic ventilatory variations seen in such periodic breathing patterns as Cheyne-Stokes respiration to improve its estimation of cardiac output.